Introduction -- Part I Preliminaries: Data -- Preprocessing -- Part II Exploratory Analysis: Principal Component Analysis -- Self-Organizing Maps -- Clustering -- Part III Modelling: Classification -- Multivariate Regression -- Part IV Model Inspection: Validation -- Variable Selection -- Part V Applications: Chemometric -- Part VI Appendices: R packages Used in This Book -- References -- Index.

"Chemometrics with R" offers readers an accessible introduction to the world of multivariate statistics in the life sciences, providing a complete description of the general data analysis paradigm, from exploratory analysis to modeling to validation. Several more specific topics from the area of chemometrics are included in a special section. The corresponding R code is provided for all the examples in the book; scripts, functions and data are available in a separate, publicly available R package. For researchers working in the life sciences, the book can also serve as an easy-to-use primer on R.